Abstract
Genetic predisposition to MDS and AML is likely polygenic and may involve several low penetrance alleles which in concert with exogenous factors result in highly variable presentation, not easily amenable to genetic studies. With the advent of whole genome scanning (WGS) technologies utilizing various SNP array (SNP-A) platforms, large scale investigations in various disorders have been conducted. In hematological malignancies to date no systematic disease-association studies using SNP-A have been reported, likely due to lower prevalence of these conditions and a highly variable phenotype. We have applied SNP-A to conduct the first GWS in MDS and MDS-derived AML with the goal to identify possible low prevalence genetic variants that contribute to the pathogenesis of these conditions and explain individual disease risk. We have studied 189 patients with MDS and secondary AML as well 119 internal controls using SNP-A. Affymetrix GeneChip 6.0 (924644 SNP probes covering most of the known LD blocks) is designed to capture 67%-89% of SNP variation among Caucasians. Following exclusion of SNP’s with a call rate of <95%, and those with serious violation of Hardy Weinberg equilibrium, single allele X2 statistics for all autosomal markers was performed. For the purpose of this study, SNP’s with minor allele frequency (MAF) <10% and p<0.001 after false discovery rate correction, were selected. Top 11 polymorphisms were chosen pointing directly to 4 genes or indirectly to informative loci through LD, informative genes include e.g., LAMC2, SGCE, FRAP1 and PTPRT. Remarkably, several informative LD blocks were also identified represented by multiple markers pointing to the presence of an informative polymorphisms in the corresponding regions. For example, 5/30 markers (all p<8×10−4) including, rs2477436, rs503243, rs3768593, rs4651151 and rs549191 are part of an LD block spanning NMAT2 and LAMC2 loci. The corresponding minor variant frequencies were 6.6% and 37.6% in homozygous and heterozygous constellation, respectively (controls: 0% and 21.6%). Second potential locus identified in our study consisted of 4 markers, all of them located on SGCE gene (rs1357318, rs2037496, rs4330611, rs13225971; p<1.9×10−4) with frequencies of homozygous variant in patients at 0.8% and 28.9% with heterozygous variant (controls 0% and 15.2%), respectively. FRAP1 (MTOR) gene was represented by singular rs3730380 marker (p=2.7×10−6), occurring at the heterozygous frequency of 17.8% vs. allelic frequency of 0% in controls. FRAP1 is a critical downstream effector of Akt involved in cell cycle regulation and angiogenesis being central regulator in PI3K/Akt/mTOR pathway. Genetic alterations of the pathway are frequent events in preneoplastic lesions and advanced cancers. Similarly, increased frequency of minor alleles of rs6030469 in PTPRT locus was found in homozygous and heterozygous constellation at 1.4% vs. 0% and 27.3% vs. 8.5% (p=4.80 × 10-5) in patients and controls, respectively. PTPRT gene was also found to be frequently mutated in cancer and is involved in growth regulation. For example, overexpression of PTPRT may lead to reduced expression of STAT3 target genes. In sum, our study constituting the first systematic approach of WGS to identify genetic risk factors in AMS and AML, suggests that several informative loci can be selected for delineation of the causative polymorphisms.
Hypothesis-free identification of modulators of genetic risk factors